What is relevance feedback?
Traditional IR systems provide a static mechanism to index documents and service retrieval requests. Relevance feedback is used to describe dynamic mechanisms that allow the retrievals to be tuned over time based on explicit or implicit feedback from the user(s). An example of implicit feedback would be where a user identifies individual documents that are relevant to their query. An example of implicit feedback would be where the system monitors the users activity to see what documents they examine, how long they spend looking at individual documents, what documents they author or perhaps a common pattern to their retrieval activity. The Probabilistic Model allows this type of explicit or implicit feedback to be injected into the retrieval process so that the weightings applied are modified, or tuned, automatically to suit a particular user’s requirements.
